Knowledge regarding cervical cancer among undergraduate female students at a selected college of Lalitpur, Nepal
Bibliographic record
Abstract
Cervical cancer is the second most common cancer in women living in less developed regions. In Nepal, little is known regarding the knowledge of cervical cancer in female young adults. A descriptive cross-sectional study was conducted to find out the knowledge regarding cervical cancer among undergraduate female students. A self-administered questionnaire was used to collect information from a non-probability sample of 150 female students from Little Angels College of Management in Lalitpur, Nepal. The data were analyzed using descriptive and inferential statistics. Among the respondents, the mean age was 19.3 ± 1.1 years. Almost all (95%) of the respondents had inadequate knowledge regarding cervical cancer. Fifty-six percent of the respondents knew the meaning of cervical cancer and 35% of the respondents had an average knowledge about risk factors. Almost two-thirds of the students knew that cervical cancer is preventable. Regarding the preventive measures, good hygiene was identified by 68.5% of respondents followed by HPV vaccine 38.3%, using condom 19.5%, and Pap smear test 8.7%. The knowledge about HPV vaccine was only told by 11.3% of respondents. There was no statistically significant association between knowledge with selected variables (age, religion, ethnicity, family income, smoking and sexual practice) in the study. Based on the findings, it is concluded that female students had inadequate knowledge regarding cervical cancer. This result reflects the need for health awareness campaigns to the students and community regarding cervical cancer, including the symptoms, causes, risk factors and preventive measures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".